We are happy to announce two distinguished speakers who
will give keynote presentations at DILS 2006.

Sponsored by

Sarah E Knoop - IBM Healthcare
Information Management

IBM Almaden Research Center, 650
Harry Rd, San Jose, CA 95120

Towards a National Healthcare
Information Infrastructure
Many countries around the world have placed an increased focus on the
need to modernize their healthcare information infrastructure. This is
particularly challenging in the United States. The U.S. healthcare
industry is by far the largest in the world in both absolute dollars
and in percentage of GDP (>$1.7T - 15% of GDP). It is also
quite fragmented and complex. This complexity, coupled with an
antiquated infrastructure for the collection of and access to medical
data, leads to enormous inefficiencies and sources of error.
Driven by consumer, regulatory, and governmental pressure, there is a
growing consensus that the time has come to modernize the US Healthcare
Information Infrastructure (HII). A modern HII will provide care givers
with better and timelier access to data. The launch of a National
Health Infrastructure Initiative (NHII) in the US in May 2004 - with
the goal of providing an electronic health record for every American
within the next decade- will eventually transform the healthcare
industry in general...just as I/T has transformed other industries in
the past. While such transformation may be disruptive in the
short term, it will in the future significantly improve the quality,
efficiency, and successful delivery of healthcare while decreasing
costs to patients and payers and improving the overall experiences of
consumers and providers. The key to this successful outcome will
be based on the way we apply I/T to healthcare data and to the services
delivered through that I/T. This must be accomplished in a way
that protects individuals, allows competition, but gives caregivers
reliable and efficient access to the data required to treat patients
and to improve the practice of medical science.

In this talk we will describe the IBM Research HII project and our
implementation of the standards for interoperability. We will also
discuss how the same infrastructure required for interoperable
electronic patient records must support the needs of medical science
and public health. This can be accomplished by building higher level
services upon a National Health Information Network, including
discovery services for medical research and data mining and modeling
services to protect populations against emerging infectious disease.

Victor Markowitz - LBNL
Biological Data Management and
Technology

An Application Driven
Perspective on Biological Data Integration
Data integration is an important part of biological applications that
acquire data generated using evolving technologies and methods or
involve data analysis across diverse specialized databases that reflect
the expertise of different groups in a specific domain. The increasing
number of such databases, the emergence of new types of data that need
to be captured, as well as the evolving biological knowledge add to the
complexity of already challenging integration problems. Furthermore,
devising solutions to these problems requires technical expertise in
several areas, such as database management systems, database
administration and software engineering, as well as data modeling and
analysis.

In practice, biological data integration is less daunting when
considered in the context of scientific applications that address
specific research questions. Established technologies and methods, such
as database management systems, data warehousing tools, and statistical
methods, have been employed successfully in developing systems that
address such questions. The key challenge is marshaling the scientific
and technical expertise required for formulating research questions,
determining the integrated data framework for answering them, and
addressing the underlying data semantics problems.

Evidence suggests that an iterative strategy based on gradually
accumulating domain specific knowledge throughout the integration
process is effective in devising solutions for application specific
biological data integration problems. This strategy will be discussed
in the context of two recently developed integrated genome systems, IMG
(http://img.jgi.doe.gov) and IMG/M
(http://img.jgi.doe.gov/m).